Tag: Visualizing

Visualization might not be the first thing a geospatial programmer thinks about, but it can still be very handy or even necessary to sometimes view or error-check one’s data. And in some cases, the main purpose of programming is to produce nice-looking maps, experiment with creative symbolizations, or batch create a series of maps or time-animations.

One way to achieve these tasks is to switch between a visual GIS software and programming, but this can be tiring and impractical in the long run. It would therefore be more helpful and productive if there were programming modules that did most of the hard work. Here are some modules that can be used to help you visualize your geographic data.

The original code was written in R and was built specifically around the Facebook dataset. This rewrite is as a Python module and is built to work on top of any dataset.

If you are looking to visualize a few (<10,000) coordinate pairs, matplotlib with basemap will be more flexible. The visualization implemented by this module is useful when the data alone are sufficient to show the geography.

The algorithm uses a heuristic which attempts to visualize the structure of the pairs rather than their relative importance. In interpreting the results, you should not come to any conclusions about the relative importance of different coordinate pairs.

The GeoRasters package is a python module that provides a fast and flexible tool to work with GIS raster files. It provides the GeoRaster class, which makes working with rasters quite transparent and easy. In a way it tries to do for rasters what GeoPandas does for geometries.

Folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the Leaflet.js library. Manipulate your data in Python, then visualize it in on a Leaflet map via Folium.